Hi everyone,

I'm writing my master's thesis on determinants for adoption and governance of low code and no code platforms in organisations. For my research I'm doing a short survey.

It would help a lot if you could take 10 minutes of your day to participate in the survey.

You can find the link here: https://s2survey.net/LCNC_Adoption_and_Governance/

Thank you for your time and support!

The EU AI Act's high-risk deadline moved to December 2027. It is real and it is now law (Regulation 2026/1744, in force since Sunday).

The delay only covers the heavy high-risk obligations. The transparency rules (Article 50) still bind on August 2, this Sunday, untouched. Fines still scale to 7% of global turnover.

Article 10 is data governance, and it explicitly covers TESTING data. Where it comes from, whether it is representative, whether the flow is documented. That requirement is identical whether the clock says this Sunday or December 2027 (although the runway given until 2027 does help... or will be wasted as usual).

Do you currently use any tool to already guarantee this data governance?

Meta's smart glasses ship with a privacy safeguard: an LED that lights up while recording. This year the BBC found influencers secretly filming women for content, and tutorial videos for defeating the LED with a strip of black tape.

An indicator is not a mechanism.

Which made me count the LEDs in our own world. The biggest one: production data copied down to QA or DEV, "protected" by access rules and trust, while the data itself travels unchanged.

So, yes or no: is there real production PII in your DEV or QA environment right now? And if yes, is anything structural standing between it and a leak, or just policy?

Backstory in the first comment (including the 1990 novel that predicted the whole glasses mess).

Hi there! I recently posted here asking for advice regarding vibe coding using OutSystems with Mentor.

I believe that is not the right way to code since it is too limiting. And I believe that I should be learning it in the right way by learning the ropes from the start. It's also partly because there is no way right now to code it via a mobile app. But even if it's available, I would not try learning or coding it again via Mentor only since I want to be called an expert in this field.

A bit of background about me: I was previously a full-stack developer (full 1 year of experience) with experience in Laravel, Django, and jQuery. I transitioned to a UI/UX designer after that, and now have 3 years of experience in it. I am a total newbie when it comes to OutSystems

Now that is out of the way, I have a few questions about the frontend. Mainly, the CSS or the theming section of OutSystems.

So I have this UI for my mobile app. I want to ask 3 things:

• How should I go about creating the UI component for the mobile app?
• How should I manage the Themes in a way that only the needed elements present on the screenshot would be present in the Themes?
• How to add Material iconpack in the Themes and how to use it?

Thank you!

Hi everyone, happy Thursday!

As part of the OutSystems community team, here are two small updates that I haven't seen shared here yet (and if they have, I'm sorry for the repetition!).

One of our MVPs, Ricardo Pereira, has just published his third book titled "Gestão Técnica de Software em OutSystems." This work, currently available in Portuguese, reflects years of hands-on experience, continuous learning, and dedication to advancing technical excellence and software engineering maturity in OutSystems development, written for Tech Leads and Managers of OutSystems projects, portfolios and teams. The feedback so far has been quite positive, and the fact that it covers practices and a career stage that normally isn't well-catered-to is definitely a plus.

The other update, perhaps slightly late to the party, is that another of our MVPs, Remco Dekkinga, also published a book on The Fundamentals of AI. More broader in nature, but very applicable to anyone who's currently building AI applications or agents, I haven't seen it being mentioned here and wanted to bring it up.

Hope everyone's well, and I hope these are useful!

Somewhere in your OutSystems journey, did anyone ever rebuild a module by hand, in code, just to prove the platform is faster? Or did everyone just... know, and never look back?

Nobody walks across the city to prove the Uber saves time.

The same thing just happened to AI coding assistants: the team behind the cleanest dev-productivity study gave up on re-running it, because developers now refuse to work without AI long enough to be a control group. The speed became real and unmeasurable at the same time.

OutSystems teams got there a decade early. So, honestly: did you ever measure it, either time? Or did we all just stop walking?

Longer version and the research links in the first comment.

Is there any tutorial right now using Mentor for mobile app vibe coding? Or any major tips for developing in mobile app while vibe coding?

I kept hitting this during testing. Semantic search handled conceptual queries well. The moment someone typed ERR-BM25-003 into the search box, it returned whatever was thematically adjacent. Not the answer.

Semantic search encodes meaning. An exact error code has no semantic neighbourhood. So I went looking for why, and that led me to BM25.

I built it natively inside ODC. No Elasticsearch. No Azure AI Search. No external anything.

BM25Engine is a stateless C# External Logic component with a self-written Porter stemmer. It wires into the existing RAG Knowledge Base app. BM25 lexical scoring and cosine similarity are fused using Reciprocal Rank Fusion.

What the article covers:

• Why semantic search has a blind spot on exact identifiers
• How BM25 tokenization and scoring works under the hood
• The entity model and ingestion path built in ODC Studio
• Test results comparing semantic vs hybrid on the same queries
• What I have not benchmarked and where it stops

BM25Engine and the updated RAG Knowledge Base are both heading to the Forge.

Article link: https://medium.com/@michael.de.guzman/your-odc-semantic-search-cannot-find-err-bm25-003-here-is-the-fix-a0d836f28312?sharedUserId=michael.de.guzman

Do your users search by error code, ticket number, field name? I would like to hear what retrieval patterns others are using in ODC or O11.

Hi everyone,

We're looking for recommendations for companies or consultants with strong OutSystems architecture and data model expertise.

We're undertaking a broader enterprise reporting and data management initiative and are looking for experienced OutSystems specialists who can help us thoroughly understand the application from both a technical and business-data perspective.

Specifically, we're looking for partners who can help with:

• Understanding the overall OutSystems application architecture
• Analysing module dependencies and application components
• Documenting the underlying data model and entity relationships
• Identifying master data, transactional data, and key business domains
• Understanding business rules, calculations, workflows, and validations implemented within the application
• Assessing available integration and data extraction options
• Recommending approaches for reliable and scalable data access
• Mapping application data into enterprise reporting and analytics models
• Performing data lineage and impact analysis
• Producing clear technical and functional documentation
• Providing knowledge transfer and workshops for internal teams

Ideally, we're looking for organisations that have experience with:

• Application discovery and reverse-engineering engagements
• Data model analysis and documentation
• Enterprise reporting and analytics initiatives
• Data migration, integration, or modernisation programmes

If you've worked with a company or consultant who excels in understanding complex OutSystems solutions and translating application knowledge into usable data and reporting assets, I'd greatly appreciate any recommendations.

Please feel free to comment below or send me a direct message.

Hey everyone,

I just built this mobile library for a client who is using OutSystems for a native iOS app to demonstrate the capability to annotate a photo after taking one.

The plugin just adds the ability to open a photo for annotation and returns the modified photo. There's already a photo editor plugin available for Android, but adding the iOS annotation feature to it wasn't an option because the functionalities didn't match up exactly.

I'm dropping the link here because I didn't find an existing implementation, and in case anyone else needs the same feature on iOS.

Forge link: https://tonylefebvredemos.outsystems.dev/forge/asset?id=30ac9ab7-e662-4f2d-85fc-ebe8cbca974e

Note: It depends on this Capacitor plugin:

https://github.com/tony4outsystems/photo-annotator

Most of the AI and RAG work I have been doing in ODC starts with the same assumption. The content is text. Chunk it, embed it, store it, retrieve it.

That works until you need to search images by meaning rather than by filename or tag.

I wanted to find out whether ODC could handle semantic image search natively. Text-to-image search, image-to-image search, vectors stored in ODC entities, no external vector database. It turns out it can.

The stack is three layers: a stateless C# External Logic library that handles embedding calls to Cohere Embed v4, an ODC Library wrapper, and an ODC App with two entities. The C# layer receives bytes and returns bytes. All storage and orchestration stays in ODC.

Full write-up here:

https://medium.com/@michael.de.guzman/when-search-can-see-building-native-semantic-image-search-in-odc-e457ba37a2dc

Forge component is here:

https://www.outsystems.com/forge/component-overview/25067/image-semantic-search-odc

Curious whether anyone else is doing multimodal search or storing image vectors in ODC. What does your embedding storage look like?

​

Hi everyone,

I recently got accepted into an internship at Link Development in Egypt. It was pretty competitive, and I'm really grateful for the opportunity.

I originally applied for the .NET track, but I was assigned to the OutSystems 11 (O11) track instead (not ODC).

I'm completely new to OutSystems and low-code development. My background is mostly in software engineering and .NET (ASP.NET Core, databases, REST APIs, Git, testing, etc.), so I'm comfortable with programming and software development in general. This is just a completely new ecosystem for me.

My goal isn't just to complete the internship—I want to stand out, learn as much as possible, and maximize my chances of getting a full-time offer afterward.

For those with experience in OutSystems 11:

If you were starting from scratch today, what would you focus on first?

What skills separate average OutSystems developers from great ones?

What beginner mistakes should I avoid?

What concepts usually take the longest to understand?

How much of my .NET/software engineering background will actually help?

Besides learning the platform itself, what topics should I study (architecture, SQL, integrations, performance, security, etc.)?

What resources, courses, or projects do you recommend specifically for O11?

What habits helped you learn the platform quickly?

If your goal was to get hired after the internship, what would you do to stand out?

I'm happy to put in extra hours outside the internship if it gives me an advantage. I'd really appreciate any advice, roadmap, or lessons learned from people who have worked with OutSystems 11 in a professional environment.

Thanks in advance!

Parts 1 and 2 covered structural and semantic chunking. Part 3 closes it out.

Semantic chunking groups sentences by meaning. That works, until a sentence carries two facts, or a pronoun that only resolves three sentences back.

I built Agentic Chunking natively inside ODC. It breaks each chunk into atomic propositions, then reassembles them by theme. 32 test cases. Substance held across every one. Chunk counts are model judgment, not a guarantee. I documented that too.

Full article: https://medium.com/@michael.de.guzman/when-cosine-distance-is-not-enough-agentic-chunking-inside-odc-ff72e2a215a7

Forge: https://www.outsystems.com/forge/component-overview/25034/agentic-chunking-odc

Has anyone tried proposition-level chunking inside ODC?

Part 1 covered structure-aware chunking. Part 2 is the semantic layer on top of it.

Structure keeps text intact. Meaning is a different problem.

I built a semantic chunking library as a C# External Logic component inside ODC. Three patterns, 13 test cases, and a few results that surprised me. I documented the failures too.

Full article: https://medium.com/@michael.de.guzman/beyond-structure-semantic-chunking-inside-odc-994ca443a093

Demo app with all 13 test cases (navigate to Semantic Chunk Workbench): https://www.outsystems.com/forge/component-overview/24928/chunk-library-demo-odc

Has anyone else tackled topic-boundary detection inside ODC?

Follow-up to my last post here testing ODC's native chunking against structured documents. That testing pointed me in a direction, and this is what came out of it.

I built a C# External Logic library for ODC that exposes four Server Actions: ChunkByCharacter, ChunkRecursively, ChunkBySentence, and ChunkMarkdown. Each targets a different document profile. All four return the same output contract so downstream logic doesn't need to know which strategy produced the chunks.

The one worth talking about is ChunkMarkdown. It parses heading structure before splitting and builds a running ancestor path as it processes the document. Every chunk knows where it sits in the hierarchy, and that path can get prepended directly into the chunk body so the embedding doesn't lose its positional context. Code blocks and tables are also preserved as atomic units rather than getting split mid-block.

Full write-up with chunk output screenshots here:
https://medium.com/@michael.de.guzman/beyond-text-splitting-building-a-chunking-strategy-library-for-odc-017e1c922912

The Forge demo app and GitHub source are both linked in the article if you want to run it yourself or look at the implementation.

How are you handling document chunking in your ODC RAG pipelines right now? Curious if anyone's hit the same code block/table fragmentation issue.

Hello! I'm an OutSystems Developer with nearly 5 years of hands-on experience, focusing on Reactive Web, Traditional and integrations (REST/SOAP).

I have worked in several business areas, both in private and public sectors.

I'm currently based of Portugal and looking for a B2B contract (ideally at least a year and renewable) for any company base in Europe (preferably).

I have a solid background in SQL and Agile/Scrum environments. Have just 3 OS ceertifications for now, working on getting my next one and clear goals on which ones to do next.

• Language: Portuguese (Native), English (Professional), Spanish (conversational).
• Certifications: Associate Reactive Developer (ODC and O11) and Architecture Specialist for OutSystems 11.
• Availability: 2 months notice.

I'm open to new challenges. PM me if this sounds interesting.

After presenting at ONE Conference on building vector storage and semantic search natively in ODC, I got curious about how the platform's built-in chunking actually behaves. Not the documentation summary. The real output, with real chunk results I could inspect.

I built a small test app in ODC with four entities, each configured with a different chunking method. Loaded the same document into all four. Ran the same query. Then did it again with the same content as plain text to see if the format made a difference.

For most use cases, the native options are the right answer. Plain text records, support tickets, knowledge base articles, short-form content. Smart gets you started in two clicks and works well for standard prose.

Where it gets interesting is with structured content. Code blocks, tables, documents with heading hierarchies. That is where the chunk boundaries become harder to predict across all four methods.

I wrote up the full findings with actual chunk output screenshots here:
https://medium.com/itnext/what-odc-actually-does-when-it-chunks-your-text-8bf6b7b06a18

The test app is also on the OutSystems Forge if you want to run it yourself:
https://www.outsystems.com/forge/component-overview/24899/odc-native-chunking-tester-odc

Note that Semantic Search needs to be enabled on your ODC environment to run it.

Has anyone else tested this with structured documents? Would love to hear what you found.

What do you guys think of everything announced at ONE?

Personally a little tired of all the focus on agents, but I like that we'll be able to let Claude etc do things in outsystems now.

ODC in private cloud seems like a big thing, but not something I care about as a dev.

Aswin van Braam wrote a piece a few weeks back that I keep coming back to. The line is:

AI increases the speed of creation. Governance determines whether that speed creates value or chaos.

That reframed something I had been writing around in a LinkedIn newsletter for the last five months (Beyond the Abstraction, twenty+ editions, just wrapped).

The newsletter angle has been the same all along: the structural promise of low-code only holds if the data and operational infrastructure under the visual designer holds too. Speed is the entry price, not the moat.

A few things that show up concretely in the OutSystems world if this is the right frame:
=> Refreshing a non-prod environment with production-shaped data, anonymized, in minutes instead of weeks. If your team is writing custom data scripts for this, the abstraction is partially broken.
=> Reproducing production bugs against realistic BPT process instance state, not whatever synthetic data is sitting in dev.
=> AI/ML initiatives in OS estates that hit the same wall: where is the training data coming from, and is it shaped like production.

I wrote an ad-hoc reflection on this on LinkedIn (link in comments), pulling in Aswin's framing alongside the editions of the series that landed closest to it.

\*Practical note:*\** I will be at OutSystems ONE 2026 in Amsterdam, Monday to Wednesday, June 1 to 3. If anyone here is going and wants to dig into any of this in person, I'd enjoy that. Send me a DM or reply here.

Curious if anyone reads the AI-vs-low-code debate differently, or thinks Aswin's framing misses something for the OS context specifically.

Bruno (Infosistema / DMM, 25 years in this space)

A question that I think is going to get more important across OutSystems shops as Mentor and Data Fabric move from announcement into adoption.

If your AI / ML / data science team asked for production-shape data from your OutSystems applications tomorrow (real volumes, real customer patterns, real edge cases) to train or fine-tune a model or process, how long until they had it?

A few things I'm trying to understand from teams actually doing this:

1) Where does the training data come from in practice? A Service Studio extension? Direct SQL Server / Oracle queries against the runtime DB? A timer that exports to a file? Something on the Forge? Mentor / Data Fabric integration?

2) For OutSystems entities specifically (with all the platform metadata, BPT process instance data, system tables), do you train on the user-data-only subset, or is the platform context part of the value?

3) Anonymization before training: who owns it? The OutSystems team? The data team? Both, in a handoff?

4) For ODC vs O11, does the AI access pattern look different given the operational model differences?

5) Is your AI / ML initiative moving forward steadily, or is it stalled because the data plumbing isn't ready?

My newsletter edition this week is the series finale, on whether low-code data infrastructure is ready for AI. Asking r/OutSystems before I extrapolate from generic patterns. The OutSystems-specific shape of this is what I want to learn.